Many IoT projects fail due to unpredictable costs. One of the elements that often weighs the most is the amount of data that is sent. These costs can be limited by an efficient way of data transfer.
When implementing large-scale IoT trajectories, the many factors in the context can create a problem with scaling. If there is no control over the costs for the data transfer or unreliable data in the initial stage, this can lead to high unforeseen costs. In addition, there are different ways to collect data from ‘devices’ and push updates to the same ‘devices’. Each method presents different challenges and a different cost structure.
With thousands of ‘devices’ and millions of messages, the costs per ‘device’ or per unit of data can add up. Only allowing data transfer to take place when it is really necessary should be the starting point. One solution is to process data at the edge of the network and only send the data when necessary. Another approach is to opt for a message standard that builds up and sends small data units at all times.
One of these messaging standards is MQTT by the way. It is an M2M messaging standard that is ideal for large-scale networks, due to very small data units. MQTT works on a publishing and subscription basis and it also features QoS, which prioritizes important data transfers. With variants of MQTT, extra efficient steps can be made, such as by using a shortened subject ID and entering this subject ID in ‘device’ and the gateway where the data is accessed. So that no unnecessary checks have to be carried out, which generate extra data.
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